Manager - Customer Service Operations

Job Description Senior Databricks Data Science Engineer (Azure AWS)

Experience

510 Years

Job Summary

We are seeking a Senior Databricks Data Science Engineer with strong hands-on experience in building scalable data engineering, analytics, and machine learning solutions using Databricks on Azure and AWS. The role involves working with large-scale datasets, advanced analytics, and ML workflows while following Agile delivery practices and ITIL service management processes.

Databricks Data Engineering Responsibilities

• Develop and maintain Databricks notebooks, workflows, and jobs
• Build ETL / ELT pipelines using Apache Spark, PySpark, Databricks SQL, and Delta Lake
• Ingest and process data from Azure Data Lake Gen2, AWS S3, relational databases, APIs, and streaming sources
• Optimize Spark workloads for performance, scalability, and cost
• Implement data validation, cleansing, and error-handling mechanisms

Data Science Machine Learning Responsibilities

• Perform exploratory data analysis (EDA) using Databricks notebooks
• Perform feature engineering and feature selection
• Build, train, evaluate, and tune machine learning models
• Use Python libraries such as Pandas, NumPy, Scikit-learn, and Spark MLlib
• Track experiments and models using MLflow

Azure AWS Integration

• Work with Azure Databricks and AWS Databricks environments
• Integrate Databricks with Azure Data Lake, Azure Synapse, and Azure Key Vault
• Integrate Databricks with AWS S3, IAM roles, and CloudWatch
• Ensure secure data access and cloud-native authentication
• Support cloud cost optimization and performance monitoring

Job Orchestration, Monitoring Support

• Create and manage Databricks Jobs and schedules
• Monitor job execution, failures, retries, and SLA adherence
• Troubleshoot Spark errors, data quality issues, and pipeline failures
• Provide production support and ensure stability of data pipelines

Process Flow Agile ITIL

• Work within Agile/Scrum teams, participating in sprint planning, stand-ups, reviews, and retrospectives
• Follow ITIL processes for Incident, Problem, Change, and Release Management
• Perform root cause analysis (RCA) for production incidents and drive preventive actions
• Ensure controlled releases and smooth promotion of data pipelines and ML models

Required Skills

• Databricks (Notebooks, Jobs, Workflows)
• Apache Spark, PySpark, Databricks SQL
• Delta Lake
• Python for data engineering and data science
• Machine learning fundamentals
• MLflow
• Azure and/or AWS cloud data services
• Git version control

Good to Have

• Delta Live Tables (DLT)
• Unity Catalog
• Spark Structured Streaming
• Advanced analytics and predictive modeling

Soft Skills

Strong analytical and problem-solving skills, ability to work with business stakeholders, good communication skills, and strong documentation practices.